The Role of Hypothesis Testing in Economic Models
Hypothesizing regarding possible economic developments in different markets can provide an understanding of the current state of an industry. While simplifications are inevitable for such an analysis, economic variables included in this process can hint toward available courses of action (Hubbard & O’Brien, 2020).
Testing Hypothesis on AI Harm for Artists
The hypothesis for this paper is the claim that the development of artificial intelligence (AI) leads to a decrease in job opportunities for commercial artists. There are numerous assumptions and predictions regarding this subject, as people fear the possibilities of future AI models (Roose, 2022). However, reviewing this phenomenon to determine its value addition or subtraction is essential.
Positive Analysis of the Hypothesis
While there are claims that AI is detrimental to professional artists, it is necessary to explore the subject further to identify what opportunities this technology provides for the market. Since positive analysis prompts one to explore realistic prospects from a course of action, it is essential to evaluate this technology as a sum of trade-offs and additions stemming from its presence on the market (Hubbard & O’Brien, 2020).
Causes of Assumption
First, the concerns that led to this hypothesis must be dismantled. Automation of the workforce is a looming threat to employees with minimal training opportunities. Yet, people currently work alongside machine-learning algorithms instead of being laid off in favor of solely autonomous systems (Roose, 2022). From a firm’s point of view, it is unreasonable to miss a chance to optimize its operational costs. Therefore, this direction makes it favorable to invest in educating the existing workers on the prospects of integrating AI into their routines.
Second, AI alone can not replace any worker in an industry, as it requires external support and guidance for training and fine-tuning. The AI and machine-learning specialist position is one of the fastest-growing jobs in the labor market, indicating that transformation, rather than replacement, is expected (Roose, 2022). It is vital to note that simplifications required to assess this economic model do not consider job satisfaction, although AI might impact it. The hypothesis appears incorrect, as job positions are not lost over AI involvement.
Evaluation of Variables
Examining variables in this hypothesis revealed a different situation that does not indicate its correctness. Li et al. (2023) state that skilled employees, who include artists, tend to “learn how to use new technologies to be more productive to stay competitive” rather than accept being replaced (p. 3). This notion highlights that AI does not threaten artists’ workflow but modifies it by providing additional tools for them to use. This notion also suggests that such a shift is inevitable, as productivity is critical for enterprises to pursue, ensuring the expansion of AI use in art and design.
Rejection of the Hypothesis
In conclusion, this tested assumption is incorrect, as artists are prompted to cooperate with AI rather than being replaced by it. The current market direction for commercial art suggests that AI-generated drawings will become integrated into artists’ workflows, allowing them to conceptualize their works faster and more efficiently. Instead of replacement, the labor market has come to a synthesis of contributions between technology and humans. While some employees may perceive this direction as adverse for their profession due to lower barriers to entry, AI does not decrease the number of available jobs in the reviewed industry.
References
Hubbard, R. G., & O’Brien, A. P. (2020). Macroeconomics (8th ed.). Pearson Education.
Li, C., Zhang, Y., Niu, X., Chen, F., & Zhou, H. (2023). Does artificial intelligence promote or inhibit on-the-Job learning? Human reactions to AI at work. Systems, 11(3). Web.
Roose, K. (2022). A.I.-generated art is already transforming creative work. The New York Times. Web.